Parkinson's disease (PD) affects about 1.5 million Americans. As PD progresses, the combined motor and non-motor symptoms often lead to decreased independence and increased reliance on caregivers and the healthcare system. Although many studies have documented the benefits of exercise, it is unclear what elements (i.e. dosage, intensity, intervention type) constitute an optimal exercise intervention for people with PD. Each individual with PD has different symptoms and capabilities which make it challenging to design a single rehabilitation program that would be optimal for all. Furthermore, progression of the disease often requires re-assessments and changes to motor rehabilitation programs. The objective of this project is to construct an instrumented cycle and use this as a clinical tool to examine the associations between rider performance and changes in motor function. This instrumented bike will be used to: 1) extract features during cycling sessions and automatically assess rider motor skills with an instrumented bike and 2) [examine the importance of motor speed variability during accelerated cadence. Individuals with Parkinson's disease will be randomized into one of two groups: 1) dynamic cycling or 2) static inertial load cycling. During dynamic cycling, motor output speed will vary. During static inertial load cycling, individuals will be directed to choose their own pedaling speed. Data from the instrumented bike will be collected continuously and motor function and balance tests will be completed before and after three exercise sessions.] The intent is to establish a comprehensive database that covers the range of expected rider capabilities. This project will provide an effective platform for researching the underlying mechanisms for improvements in motor function and for readily implementing a feedback system that can dynamically optimize the benefits of exercise in individuals with Parkinson's disease and other neurological disorders.